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• W3083778346 abstract "The rocketing number of photos shared on social media leads to the increasing demand for photo editing. We here focus on a specific scenario - group dinner photo and tackle two user-demanding problems - to add a person or replace the tabletop. The target objects are determined according to the saliency detection results. We developed a novel application to solve these problems. With our system, non-professional users can accomplish semantic editing within a few seconds, including inserting human and tidying up tabletops. Our system contributes to the state-of-the-art by (1) efficiently selecting the saliency area by its semantic meaning, (2) accurately compositing the salient content with the target image, based on the contextual knowledge. The context refers to the key factors, including occlusion and artifacts during the composition. The feedback from users shows that the authenticity of inserting human is satisfying. A comparative study shows that our system can more efficiently produce pictures with comparable quality as those edited by professional editing software in the tidying up tabletops work." @default.
• W3083778346 created "2020-09-14" @default.
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• W3083778346 date "2021-09-01" @default.
• W3083778346 modified "2023-10-16" @default.
• W3083778346 title "Salient object segmentation for image composition: A case study of group dinner photo" @default.
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• W3083778346 doi "https://doi.org/10.1016/j.neucom.2020.06.127" @default.
• W3083778346 hasPublicationYear "2021" @default.
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